Many genes are related via common regulation, common functional molecular mechanisms, and common pathways. Understanding the relationship between genes is important for biological research and has extensive practical application in drug development and diagnostics.
MicroRNAs are a recently identified class of regulatory RNAs that target specific mRNAs for degradation or inhibition of translation, resulting in a decrease of the protein encoded by the target mRNA. Current estimates are that 30% or more of human mRNAs are regulated by miRNAs (Lewis et al., Cell 120:15-20 (2005). Studies investigating expression profiles of various miRNAs in normal and cancer cells reveals that miRNA expression patterns may have clinical relevance. (See, e.g., Yanaihara, N. et al., Cancer Cell 9:189-198, 2006). Application of various bioinformatics approaches have revealed that a single miRNA might bind to as many as 200 gene targets and these targets are often diverse in function, including, for example, transcription factors, secreted factors, receptors and transporters (see, e.g., Esquela-Kerscher and Slack, Nature Reviews 6:259-269 (2006); Baretl, D. P. et al., Nat Rev Genet 5(5):396-400 (2004)). Therefore, the deletion or overexpression of a particular miRNA is likely to be pleotropic.
To date, over 200 microRNAs have been described in humans, however, the current state of knowledge regarding microRNA targets and the determination of microRNA functions is incomplete. Although thousands of miRNA targets have been predicted using computational methods, relatively few predications have been experimentally validated. Computational methods are not optimal for predicting miRNA target sites. Bioinformatics approaches generally rely heavily on the detection of seed region (the encompasses the first 1-12 bases of the mature miRNA sequence) complementary motifs that are conserved in the 3′ UTR sequences of genes across divergent species (see, e.g., John, B. et al., PloS Biol 2(11):e363, 2004). Therefore, such methods are not predictive for microRNA targets sites that are not conserved across species, or for identifying target sites that are not perfectly matched with seed regions. Moreover, target prediction using different computational methods often do not agree. Since relatively few predicted microRNA: target interactions have been experimentally confirmed, it is difficult to know how accurate such predictions are. Available methods for validation are laborious and not easily amenable to high-throughput methodologies (see e.g., Bentwich, I., FEBS Lett 579:5904-5910 (2005)).
It is important to assign functions to miRNAs and to accurately identify miRNA responsive targets. Since a single miRNA can regulate hundreds of targets, understanding of biological pathways regulated by microRNAs is not obiouvs from examination of their targets. As functions are assigned to miRNAs, it is also important to determine which of their target(s) are responsible for a phenotype. It is also currently unknown whether the numerous miRNA responsive targets act individually or in concert.